MindMap Gallery Data Structures and Algorithms
Data Structures and Algorithms Data structures are the way data is stored and organized in computers. A data structure is a collection of data elements that has certain logical relationships, applies a certain storage structure in the computer, and encapsulates corresponding operations.
Edited at 2022-06-01 17:11:27This is a panoramic infographic—currently sweeping across the web—illustrating the comprehensive applications of OpenClaw, a popular open-source AI agent platform. It systematically introduces this intelligent agent framework—affectionately dubbed "Lobster Farming"—helping readers quickly grasp its core value, technical features, application scenarios, and security protocols. It serves as an excellent introductory guide and practical manual.
這是一張最近風靡全網關於熱門開源AI代理平台OpenClaw的全網應用全景圖解。它系統性地介紹了這款被稱為「養龍蝦」的智慧體框架,幫助讀者快速理解其核心價值、技術特性、應用場景及安全規範,是一份極佳的入門指南與實操手冊。此圖主要針對希望利用AI建構自動化工作流程的技術從業人員、中小企業主及效率追求者,透過9大模組層層遞進,全面剖析了OpenClaw從概念到落地的整個過程。 圖中核心內容首先釐清了「養龍蝦」指涉的是OpenClawd開源智能體,並強調其本質是「AI基建」而非一般聊天機器人。隨後詳細比較其與傳統AI助理的區別,擁有記憶管理、權限控制、會話隔離和異常恢復四大基礎能力,支援跨平台存取和多模型相容(如GPT、Claude、Ollama)。同時,圖解提供了完整的部署方案(雲端/本地/Docker),並列舉了辦公室自動化、內容創作、資料收集等五大應用程式場景。此外,還展示了其火爆程度、政府與大廠佈局、安全部署建議及適合/不適合的人群分類。幫助你快速掌握OpenClaw技術架構與應用價值,指導個人或企業建構AI自動化系統,規避資料外洩與權限失控風險,是學習「執行式AI」轉型的權威參考圖譜。
本圖由萬興腦圖繪製,是針對IT研發崗位的結構化個人履歷模板,完整涵蓋求職核心資訊模組。基本資訊區包含姓名、電話、信箱、求職意願及GitHub連結;專業概要要求以2-3句提煉核心優勢;工作經驗以「公司A高級Java開發工程師」為例,以「透過(行動),達成(量化成果)」格式呈現微服務架構設計、系統效能優化、團隊技術規範制定等職責,公司B經歷則聚焦功能模組開發與Elasticsearch搜尋優化;技能專長分程式語言、後端框架、中介軟體、資料庫、容器雲等維度,清楚展示技術堆疊;專案成果以「電商平台秒殺系統」為例,說明技術棧、架構設計、個人貢獻(Redis Lua庫存原子扣減)及KPI;教育背景包含一流大學電腦專業學歷,以及AWS認證解決方案架構師、軟考中級軟體設計師證書。模板邏輯嚴謹,涵蓋IT研發求職全流程關鍵訊息,幫助求職者清晰、量化展示專業能力。
This is a panoramic infographic—currently sweeping across the web—illustrating the comprehensive applications of OpenClaw, a popular open-source AI agent platform. It systematically introduces this intelligent agent framework—affectionately dubbed "Lobster Farming"—helping readers quickly grasp its core value, technical features, application scenarios, and security protocols. It serves as an excellent introductory guide and practical manual.
這是一張最近風靡全網關於熱門開源AI代理平台OpenClaw的全網應用全景圖解。它系統性地介紹了這款被稱為「養龍蝦」的智慧體框架,幫助讀者快速理解其核心價值、技術特性、應用場景及安全規範,是一份極佳的入門指南與實操手冊。此圖主要針對希望利用AI建構自動化工作流程的技術從業人員、中小企業主及效率追求者,透過9大模組層層遞進,全面剖析了OpenClaw從概念到落地的整個過程。 圖中核心內容首先釐清了「養龍蝦」指涉的是OpenClawd開源智能體,並強調其本質是「AI基建」而非一般聊天機器人。隨後詳細比較其與傳統AI助理的區別,擁有記憶管理、權限控制、會話隔離和異常恢復四大基礎能力,支援跨平台存取和多模型相容(如GPT、Claude、Ollama)。同時,圖解提供了完整的部署方案(雲端/本地/Docker),並列舉了辦公室自動化、內容創作、資料收集等五大應用程式場景。此外,還展示了其火爆程度、政府與大廠佈局、安全部署建議及適合/不適合的人群分類。幫助你快速掌握OpenClaw技術架構與應用價值,指導個人或企業建構AI自動化系統,規避資料外洩與權限失控風險,是學習「執行式AI」轉型的權威參考圖譜。
本圖由萬興腦圖繪製,是針對IT研發崗位的結構化個人履歷模板,完整涵蓋求職核心資訊模組。基本資訊區包含姓名、電話、信箱、求職意願及GitHub連結;專業概要要求以2-3句提煉核心優勢;工作經驗以「公司A高級Java開發工程師」為例,以「透過(行動),達成(量化成果)」格式呈現微服務架構設計、系統效能優化、團隊技術規範制定等職責,公司B經歷則聚焦功能模組開發與Elasticsearch搜尋優化;技能專長分程式語言、後端框架、中介軟體、資料庫、容器雲等維度,清楚展示技術堆疊;專案成果以「電商平台秒殺系統」為例,說明技術棧、架構設計、個人貢獻(Redis Lua庫存原子扣減)及KPI;教育背景包含一流大學電腦專業學歷,以及AWS認證解決方案架構師、軟考中級軟體設計師證書。模板邏輯嚴謹,涵蓋IT研發求職全流程關鍵訊息,幫助求職者清晰、量化展示專業能力。
Algorithms and Data Structures
linear table
Linked linear list has head node (pacesetter)
The first node is phead->next or head.next
stack
Non-recursive implementation of recursive programs does not necessarily require a stack
You can use the idea of DP
picture
The vertex set of the graph is not empty, so there is no empty graph
connected components
Maximally connected subgraph
A circuit is a ring
The cycle must not be a simple path
Except for the endpoints, the intermediate nodes of a simple loop do not repeat.
The vertices of a simple path are not repeated
adjacency matrix
Generally, the elements on the main diagonal are 0
Not connected is infinity
Critical Path
Earliest start time ve()
Latest start time vl()
The earliest start time of the activity e()
The earliest start time of the origin point
The latest start time of the activity l()
The latest start time of the meeting point minus the activity time
Activity time margin d()
Indicates the time margin of the activity. An activity with a margin of 0 is on the critical path.
Shortening the common edges of all critical paths can shorten the construction period
Extending any critical edge will extend the construction period
KMP
partial match table
A table consisting of the common prefix and suffix lengths of all prefixes of the substring
next[]
nextval[]
sort
Hill sort
an insertion sort
Gradually reduce the increment and use direct insertion sort within the group
external sort
multi-way balanced merging
The number of segments after each pass of processing becomes celing(m/k), where k is the number of passes.
Find
average search length
binary search
Draw search tree
Also known as binary decision tree
The average height of the failed node's parent node
Success is calculated as average depth
Hash table lookup
Tree
B-tree and B-tree
B-tree
Definition of m-order B-tree
Each node has at most m subtrees and m-1 keywords
The non-empty B-tree root node has at least 2 subtrees
The non-root node has at least ceiling(m/2) subtrees
3,4-2
5-3
The leaf node is the node where the search failed (actually does not exist)
The terminal node refers to the lowest node
Also called B-tree
Each element appears only once
Data is inside the B-tree node
Any node keyword always has left and right children
The predecessor/successor of any keyword is always at the lowest level
Split on insertion
Middle elements are raised, recursively split
After splitting, the node on the left is always full.
The 4th order B-tree node is split into 2,1,1
merge on delete
always translates into a merger from the bottom
If you have enough, borrow it from your brothers
If the borrowing is not enough, the parent keyword will be dropped and the terminal point will be merged.
If there is not enough money to borrow, it will definitely be merged.
The order is odd, and there are m-1 keywords after merging.
The order is even, and there are m-2 keywords after merging.
Note that the nodes after merging even-order B-trees are not full.
Merge towards the root
B-tree
m-order B-tree definition
Similarly, there are at most m subtrees and at least ceiling(m/2) subtrees.
But the keyword is the largest keyword corresponding to the child node
Therefore there are also m
Leaf nodes have pointers to records
Leaf nodes are linked horizontally to facilitate traversal search
Pay attention to the difference between the leaf nodes of the B tree and the leaf nodes of the B tree.
minimum spanning tree
When the weights of each edge are different from each other, the minimum spanning tree is unique
The spanning trees constructed using Prim's algorithm from different vertices are not necessarily the same.
The minimum spanning tree edge weight sequence of the same picture is the same
heap
Build a pile
Array traversal from back to front
AVL tree
Delete and insert
If the deleted node is a non-leaf node, the tree may be the same after reinsertion